In-band wormhole detection in wireless ad hoc networks using change point detection method

In-band wormhole detection in wireless ad hoc networks using change point detection method
复制标题

使用变点检测方法的无线自组织网络中的带内虫洞检测

DOI:
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发表时间:
2016
期刊:
2016 IEEE International Conference on Communications (ICC)
影响因子:
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通讯作者:
W. Wu
W. Wu
中科院分区:
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文献类型:
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作者:
M. Cheng;Yizong Ling;W. Wu

文献摘要

被引文献

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本文研究了无线自组织网络中带内虫洞的检测问题。该检测方案需要在接收端收集数据包的端到端延迟,然后应用顺序变化点检测算法来检测延迟时间序列中的突变。提出了一种新的变点检测算法SW-CLT。该算法是基于中心极限定理(CLT),不涉及使用预先设定的检测阈值。该算法与非参数累积和(NP-Cumulum)相比,因为非参数版本被认为是更强大的高度动态数据比参数版本。SW-CLT能够根据数据的方差调整其检测阈值,因此比使用预设阈值的NP-CLUM更鲁棒。ns 3的仿真结果验证了SW-CLT在所有模拟场景中优于NP-CNOUM。
This paper addresses detecting in-band wormholes in wireless ad hoc networks. The detection scheme requires collecting the end-to-end delay of packets at the receiver and then applying a sequential change point detection algorithm to detect abrupt changes in the delay time series. A new change point detection algorithm, named SW-CLT, is proposed. The algorithm is based on the Central Limit Theorem (CLT) and does not involve using a preset detecting threshold. The algorithm is compared with the non-parametric cumulative sum (NP-CUSUM) because the non-parametric version is believed to be more robust to highly dynamic data than the parametric version. SW-CLT has the ability to adjust its detection threshold with the variance of the data, and therefore is more robust than NP-CUSUM, which uses a preset threshold. Simulation results from ns3 verified the advantage of SW-CLT over NP-CUSUM in all simulated scenarios.